{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/"
    },
    "executionInfo": {
     "elapsed": 19025,
     "status": "ok",
     "timestamp": 1674675438915,
     "user": {
      "displayName": "Amera Al-Amery",
      "userId": "17271150753343271230"
     },
     "user_tz": 300
    },
    "id": "P8rZ7rJhbvBp",
    "outputId": "0de17656-345f-4fdc-c178-8328dedd42f2"
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Mounted at /content/drive\n"
     ]
    }
   ],
   "source": [
    "from google.colab import drive\n",
    "drive.mount('/content/drive')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/",
     "height": 148
    },
    "executionInfo": {
     "elapsed": 136,
     "status": "error",
     "timestamp": 1674675441028,
     "user": {
      "displayName": "Amera Al-Amery",
      "userId": "17271150753343271230"
     },
     "user_tz": 300
    },
    "id": "0eb9dafd",
    "outputId": "ec8a4e4b-01b3-4cc6-dcfc-d3ee45d29293"
   },
   "outputs": [
    {
     "ename": "SyntaxError",
     "evalue": "ignored",
     "output_type": "error",
     "traceback": [
      "\u001b[0;36m  File \u001b[0;32m\"<ipython-input-3-abeb1316bdfa>\"\u001b[0;36m, line \u001b[0;32m6\u001b[0m\n\u001b[0;31m    ''''\u001b[0m\n\u001b[0m        \n^\u001b[0m\n\u001b[0;31mSyntaxError\u001b[0m\u001b[0;31m:\u001b[0m EOL while scanning string literal\n"
     ]
    }
   ],
   "source": [
    "''''\n",
    "The code below find the risk level for each county for one week before the considered switch date \n",
    "Example:\n",
    "fips:1001 categorized as A means Recomm-Mandate\n",
    "bring the date of switch and find average of risk level befor thet date, then categorize it to Low, mid, high, extreme, critical \n",
    "''''"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/"
    },
    "executionInfo": {
     "elapsed": 1154,
     "status": "ok",
     "timestamp": 1674675472770,
     "user": {
      "displayName": "Amera Al-Amery",
      "userId": "17271150753343271230"
     },
     "user_tz": 300
    },
    "id": "-MiQ2yxMbm_F",
    "outputId": "7e1af247-aef6-46f2-89a7-daf68a2f0cd1"
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Drive already mounted at /content/drive; to attempt to forcibly remount, call drive.mount(\"/content/drive\", force_remount=True).\n"
     ]
    }
   ],
   "source": [
    "from google.colab import drive\n",
    "drive.mount('/content/drive')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {
    "executionInfo": {
     "elapsed": 9272,
     "status": "ok",
     "timestamp": 1674675511618,
     "user": {
      "displayName": "Amera Al-Amery",
      "userId": "17271150753343271230"
     },
     "user_tz": 300
    },
    "id": "9ca5487b"
   },
   "outputs": [],
   "source": [
    "import pandas as pd\n",
    "import numpy as np\n",
    "import datetime as dt\n",
    "import matplotlib.pylab as plt\n",
    "\n",
    "##############################################################################\n",
    "#COVID\n",
    "\n",
    "risk = pd.read_csv(\"/content/drive/MyDrive/Colab Notebooks/Mask_Project/counties.timeseries.csv\")\n",
    "#risk=pd.read_csv(\"C:/Users/nimda/Desktop/Research_2/Data/clustering results/cases_datasets/death_per_100k.csv\")\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "id": "7d771ef9"
   },
   "outputs": [],
   "source": [
    "risk1=risk[0:1000000]\n",
    "risk2=risk[1000000:1758276]\n",
    "risk3=risk[1758277:]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {
    "executionInfo": {
     "elapsed": 504,
     "status": "ok",
     "timestamp": 1674675518032,
     "user": {
      "displayName": "Amera Al-Amery",
      "userId": "17271150753343271230"
     },
     "user_tz": 300
    },
    "id": "6dfb8128"
   },
   "outputs": [],
   "source": [
    "risk['date'] = pd.to_datetime(risk['date'])\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {
    "executionInfo": {
     "elapsed": 127,
     "status": "ok",
     "timestamp": 1674675519291,
     "user": {
      "displayName": "Amera Al-Amery",
      "userId": "17271150753343271230"
     },
     "user_tz": 300
    },
    "id": "02dd597f"
   },
   "outputs": [],
   "source": [
    "# first convert strings to actual dates\n",
    "risk['date'] = pd.to_datetime(risk['date'],format = '%m/%d/%Y') \n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "e5562af4"
   },
   "source": [
    "##Bring the level for each county befor its recommended exact date instesd of fixed period (for counties with recommended only policy)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {
    "executionInfo": {
     "elapsed": 717,
     "status": "ok",
     "timestamp": 1674675686396,
     "user": {
      "displayName": "Amera Al-Amery",
      "userId": "17271150753343271230"
     },
     "user_tz": 300
    },
    "id": "17ac3f3a"
   },
   "outputs": [],
   "source": [
    "recom_start_date=pd.read_csv(\"/content/drive/MyDrive/Colab Notebooks/Mask_Project/recommended_start_date.csv\")\n",
    "# bring counties which implemented recommended only without any mask mandate..\n",
    "\n",
    "recomm_fips=pd.read_excel(\"/content/drive/MyDrive/Colab Notebooks/Mask_Project/recommended_just_mask_fips_counties.xlsx\")\n",
    "\n",
    "fips=np.unique(recom_start_date['fips'])\n",
    "\n",
    "# keep counties that applied recommended mask only\n",
    "recom_start_date= recom_start_date.merge(recomm_fips, on = 'fips', how='right')\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/"
    },
    "executionInfo": {
     "elapsed": 172,
     "status": "ok",
     "timestamp": 1674675700921,
     "user": {
      "displayName": "Amera Al-Amery",
      "userId": "17271150753343271230"
     },
     "user_tz": 300
    },
    "id": "881b4bd5",
    "outputId": "3dea9122-bc91-47a3-f802-07c928771b3a"
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "538"
      ]
     },
     "execution_count": 12,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "len(recom_start_date['fips'])\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {
    "executionInfo": {
     "elapsed": 139,
     "status": "ok",
     "timestamp": 1674675706089,
     "user": {
      "displayName": "Amera Al-Amery",
      "userId": "17271150753343271230"
     },
     "user_tz": 300
    },
    "id": "edaa110a"
   },
   "outputs": [],
   "source": [
    "\n",
    "\n",
    "dic_start_date={}\n",
    "for i in range(len(recom_start_date)):\n",
    "    recomm_date=recom_start_date.iloc[i]['res_recomm']\n",
    "    fips= recom_start_date.iloc[i]['fips']\n",
    "    dic_start_date.setdefault(fips, [])\n",
    "\n",
    "    dic_start_date[fips].append(recomm_date)\n",
    "\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {
    "executionInfo": {
     "elapsed": 1,
     "status": "ok",
     "timestamp": 1674675707988,
     "user": {
      "displayName": "Amera Al-Amery",
      "userId": "17271150753343271230"
     },
     "user_tz": 300
    },
    "id": "28a6a880"
   },
   "outputs": [],
   "source": [
    "# counties with recommended only, we consider mask recommended date to get the risk level before "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/"
    },
    "executionInfo": {
     "elapsed": 5073,
     "status": "ok",
     "timestamp": 1674675757331,
     "user": {
      "displayName": "Amera Al-Amery",
      "userId": "17271150753343271230"
     },
     "user_tz": 300
    },
    "id": "75c94d87",
    "outputId": "006b2a3b-91b3-4217-fc74-f29312558215"
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "DatetimeIndex(['2020-04-02'], dtype='datetime64[ns]', freq=None)\n",
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      "DatetimeIndex(['2020-05-01'], dtype='datetime64[ns]', freq=None)\n",
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      "DatetimeIndex(['2020-05-01'], dtype='datetime64[ns]', freq=None)\n",
      "DatetimeIndex(['2020-05-01'], dtype='datetime64[ns]', freq=None)\n",
      "DatetimeIndex(['2020-05-01'], dtype='datetime64[ns]', freq=None)\n",
      "DatetimeIndex(['2020-05-01'], dtype='datetime64[ns]', freq=None)\n",
      "DatetimeIndex(['2020-05-01'], dtype='datetime64[ns]', freq=None)\n",
      "DatetimeIndex(['2020-05-01'], dtype='datetime64[ns]', freq=None)\n",
      "DatetimeIndex(['2020-05-01'], dtype='datetime64[ns]', freq=None)\n",
      "DatetimeIndex(['2020-05-01'], dtype='datetime64[ns]', freq=None)\n",
      "DatetimeIndex(['2020-05-01'], dtype='datetime64[ns]', freq=None)\n",
      "DatetimeIndex(['2020-05-01'], dtype='datetime64[ns]', freq=None)\n",
      "DatetimeIndex(['2020-05-01'], dtype='datetime64[ns]', freq=None)\n",
      "DatetimeIndex(['2020-05-01'], dtype='datetime64[ns]', freq=None)\n",
      "DatetimeIndex(['2020-05-01'], dtype='datetime64[ns]', freq=None)\n",
      "DatetimeIndex(['2020-05-01'], dtype='datetime64[ns]', freq=None)\n",
      "DatetimeIndex(['2020-05-01'], dtype='datetime64[ns]', freq=None)\n",
      "DatetimeIndex(['2020-05-01'], dtype='datetime64[ns]', freq=None)\n",
      "DatetimeIndex(['2020-05-01'], dtype='datetime64[ns]', freq=None)\n",
      "DatetimeIndex(['2020-05-01'], dtype='datetime64[ns]', freq=None)\n",
      "DatetimeIndex(['2020-05-01'], dtype='datetime64[ns]', freq=None)\n",
      "DatetimeIndex(['2020-05-01'], dtype='datetime64[ns]', freq=None)\n",
      "DatetimeIndex(['2020-05-01'], dtype='datetime64[ns]', freq=None)\n",
      "DatetimeIndex(['2020-05-01'], dtype='datetime64[ns]', freq=None)\n",
      "DatetimeIndex(['2020-05-01'], dtype='datetime64[ns]', freq=None)\n",
      "DatetimeIndex(['2020-05-01'], dtype='datetime64[ns]', freq=None)\n",
      "DatetimeIndex(['2020-05-01'], dtype='datetime64[ns]', freq=None)\n",
      "DatetimeIndex(['2020-05-01'], dtype='datetime64[ns]', freq=None)\n",
      "DatetimeIndex(['2020-05-01'], dtype='datetime64[ns]', freq=None)\n",
      "DatetimeIndex(['2020-05-01'], dtype='datetime64[ns]', freq=None)\n",
      "DatetimeIndex(['2020-05-01'], dtype='datetime64[ns]', freq=None)\n",
      "DatetimeIndex(['2020-05-01'], dtype='datetime64[ns]', freq=None)\n",
      "DatetimeIndex(['2020-05-01'], dtype='datetime64[ns]', freq=None)\n",
      "DatetimeIndex(['2020-05-01'], dtype='datetime64[ns]', freq=None)\n",
      "DatetimeIndex(['2020-05-01'], dtype='datetime64[ns]', freq=None)\n",
      "DatetimeIndex(['2020-05-01'], dtype='datetime64[ns]', freq=None)\n",
      "DatetimeIndex(['2020-05-01'], dtype='datetime64[ns]', freq=None)\n",
      "DatetimeIndex(['2020-05-01'], dtype='datetime64[ns]', freq=None)\n",
      "DatetimeIndex(['2020-05-01'], dtype='datetime64[ns]', freq=None)\n",
      "DatetimeIndex(['2020-05-01'], dtype='datetime64[ns]', freq=None)\n",
      "DatetimeIndex(['2020-05-01'], dtype='datetime64[ns]', freq=None)\n",
      "DatetimeIndex(['2020-05-01'], dtype='datetime64[ns]', freq=None)\n",
      "DatetimeIndex(['2020-05-01'], dtype='datetime64[ns]', freq=None)\n",
      "DatetimeIndex(['2020-05-01'], dtype='datetime64[ns]', freq=None)\n",
      "DatetimeIndex(['2020-05-01'], dtype='datetime64[ns]', freq=None)\n",
      "DatetimeIndex(['2020-05-01'], dtype='datetime64[ns]', freq=None)\n",
      "DatetimeIndex(['2020-05-01'], dtype='datetime64[ns]', freq=None)\n",
      "DatetimeIndex(['2020-05-01'], dtype='datetime64[ns]', freq=None)\n",
      "DatetimeIndex(['2020-05-01'], dtype='datetime64[ns]', freq=None)\n",
      "DatetimeIndex(['2020-05-01'], dtype='datetime64[ns]', freq=None)\n",
      "DatetimeIndex(['2020-05-01'], dtype='datetime64[ns]', freq=None)\n",
      "DatetimeIndex(['2020-05-01'], dtype='datetime64[ns]', freq=None)\n",
      "DatetimeIndex(['2020-05-01'], dtype='datetime64[ns]', freq=None)\n",
      "DatetimeIndex(['2020-05-01'], dtype='datetime64[ns]', freq=None)\n",
      "DatetimeIndex(['2020-05-01'], dtype='datetime64[ns]', freq=None)\n",
      "DatetimeIndex(['2020-05-01'], dtype='datetime64[ns]', freq=None)\n",
      "DatetimeIndex(['2020-05-01'], dtype='datetime64[ns]', freq=None)\n",
      "DatetimeIndex(['2020-05-01'], dtype='datetime64[ns]', freq=None)\n",
      "DatetimeIndex(['2020-05-01'], dtype='datetime64[ns]', freq=None)\n",
      "DatetimeIndex(['2020-05-01'], dtype='datetime64[ns]', freq=None)\n",
      "DatetimeIndex(['2020-05-01'], dtype='datetime64[ns]', freq=None)\n",
      "DatetimeIndex(['2020-05-01'], dtype='datetime64[ns]', freq=None)\n",
      "DatetimeIndex(['2020-05-01'], dtype='datetime64[ns]', freq=None)\n",
      "DatetimeIndex(['2020-04-08'], dtype='datetime64[ns]', freq=None)\n",
      "DatetimeIndex(['2020-04-29'], dtype='datetime64[ns]', freq=None)\n",
      "DatetimeIndex(['2020-04-29'], dtype='datetime64[ns]', freq=None)\n",
      "DatetimeIndex(['2020-04-07'], dtype='datetime64[ns]', freq=None)\n",
      "DatetimeIndex(['2020-04-29'], dtype='datetime64[ns]', freq=None)\n",
      "DatetimeIndex(['2020-04-29'], dtype='datetime64[ns]', freq=None)\n",
      "DatetimeIndex(['2020-04-04'], dtype='datetime64[ns]', freq=None)\n",
      "DatetimeIndex(['2020-04-29'], dtype='datetime64[ns]', freq=None)\n",
      "DatetimeIndex(['2020-04-29'], dtype='datetime64[ns]', freq=None)\n",
      "DatetimeIndex(['2020-04-29'], dtype='datetime64[ns]', freq=None)\n",
      "DatetimeIndex(['2020-04-06'], dtype='datetime64[ns]', freq=None)\n",
      "DatetimeIndex(['2020-04-29'], dtype='datetime64[ns]', freq=None)\n",
      "DatetimeIndex(['2020-04-16'], dtype='datetime64[ns]', freq=None)\n",
      "DatetimeIndex(['2020-04-29'], dtype='datetime64[ns]', freq=None)\n",
      "DatetimeIndex(['2020-04-29'], dtype='datetime64[ns]', freq=None)\n",
      "DatetimeIndex(['2020-04-29'], dtype='datetime64[ns]', freq=None)\n",
      "DatetimeIndex(['2020-04-14'], dtype='datetime64[ns]', freq=None)\n",
      "DatetimeIndex(['2020-04-29'], dtype='datetime64[ns]', freq=None)\n",
      "DatetimeIndex(['2020-04-29'], dtype='datetime64[ns]', freq=None)\n",
      "DatetimeIndex(['2020-04-29'], dtype='datetime64[ns]', freq=None)\n",
      "DatetimeIndex(['2020-04-29'], dtype='datetime64[ns]', freq=None)\n",
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      "DatetimeIndex(['2020-04-29'], dtype='datetime64[ns]', freq=None)\n",
      "DatetimeIndex(['2020-04-29'], dtype='datetime64[ns]', freq=None)\n",
      "DatetimeIndex(['2020-04-29'], dtype='datetime64[ns]', freq=None)\n",
      "DatetimeIndex(['2020-04-29'], dtype='datetime64[ns]', freq=None)\n",
      "DatetimeIndex(['2020-04-29'], dtype='datetime64[ns]', freq=None)\n",
      "DatetimeIndex(['2020-04-29'], dtype='datetime64[ns]', freq=None)\n",
      "DatetimeIndex(['2020-04-29'], dtype='datetime64[ns]', freq=None)\n",
      "DatetimeIndex(['2020-04-29'], dtype='datetime64[ns]', freq=None)\n",
      "DatetimeIndex(['2020-04-29'], dtype='datetime64[ns]', freq=None)\n",
      "DatetimeIndex(['2020-04-29'], dtype='datetime64[ns]', freq=None)\n",
      "DatetimeIndex(['2020-04-29'], dtype='datetime64[ns]', freq=None)\n",
      "DatetimeIndex(['2020-04-29'], dtype='datetime64[ns]', freq=None)\n",
      "DatetimeIndex(['2020-04-29'], dtype='datetime64[ns]', freq=None)\n",
      "DatetimeIndex(['2020-04-29'], dtype='datetime64[ns]', freq=None)\n",
      "DatetimeIndex(['2020-04-29'], dtype='datetime64[ns]', freq=None)\n",
      "DatetimeIndex(['2020-04-29'], dtype='datetime64[ns]', freq=None)\n",
      "DatetimeIndex(['2020-04-29'], dtype='datetime64[ns]', freq=None)\n",
      "DatetimeIndex(['2020-04-29'], dtype='datetime64[ns]', freq=None)\n",
      "DatetimeIndex(['2020-04-29'], dtype='datetime64[ns]', freq=None)\n",
      "DatetimeIndex(['2020-04-29'], dtype='datetime64[ns]', freq=None)\n",
      "DatetimeIndex(['2020-04-29'], dtype='datetime64[ns]', freq=None)\n",
      "DatetimeIndex(['2020-04-29'], dtype='datetime64[ns]', freq=None)\n",
      "DatetimeIndex(['2020-04-29'], dtype='datetime64[ns]', freq=None)\n",
      "DatetimeIndex(['2020-04-29'], dtype='datetime64[ns]', freq=None)\n",
      "DatetimeIndex(['2020-04-29'], dtype='datetime64[ns]', freq=None)\n",
      "DatetimeIndex(['2020-04-29'], dtype='datetime64[ns]', freq=None)\n",
      "DatetimeIndex(['2020-04-29'], dtype='datetime64[ns]', freq=None)\n",
      "DatetimeIndex(['2020-04-29'], dtype='datetime64[ns]', freq=None)\n",
      "DatetimeIndex(['2020-04-29'], dtype='datetime64[ns]', freq=None)\n",
      "DatetimeIndex(['2020-04-29'], dtype='datetime64[ns]', freq=None)\n",
      "DatetimeIndex(['2020-04-29'], dtype='datetime64[ns]', freq=None)\n",
      "DatetimeIndex(['2020-04-29'], dtype='datetime64[ns]', freq=None)\n",
      "DatetimeIndex(['2020-04-29'], dtype='datetime64[ns]', freq=None)\n",
      "DatetimeIndex(['2020-04-29'], dtype='datetime64[ns]', freq=None)\n",
      "DatetimeIndex(['2020-04-29'], dtype='datetime64[ns]', freq=None)\n",
      "DatetimeIndex(['2020-04-29'], dtype='datetime64[ns]', freq=None)\n",
      "DatetimeIndex(['2020-04-29'], dtype='datetime64[ns]', freq=None)\n",
      "DatetimeIndex(['2020-04-29'], dtype='datetime64[ns]', freq=None)\n",
      "DatetimeIndex(['2020-04-29'], dtype='datetime64[ns]', freq=None)\n",
      "DatetimeIndex(['2020-04-29'], dtype='datetime64[ns]', freq=None)\n",
      "DatetimeIndex(['2020-04-29'], dtype='datetime64[ns]', freq=None)\n",
      "DatetimeIndex(['2020-04-29'], dtype='datetime64[ns]', freq=None)\n",
      "DatetimeIndex(['2020-04-29'], dtype='datetime64[ns]', freq=None)\n",
      "DatetimeIndex(['2020-04-29'], dtype='datetime64[ns]', freq=None)\n",
      "DatetimeIndex(['2020-04-29'], dtype='datetime64[ns]', freq=None)\n",
      "DatetimeIndex(['2020-04-29'], dtype='datetime64[ns]', freq=None)\n",
      "DatetimeIndex(['2020-04-29'], dtype='datetime64[ns]', freq=None)\n",
      "DatetimeIndex(['2020-04-29'], dtype='datetime64[ns]', freq=None)\n",
      "DatetimeIndex(['2020-04-29'], dtype='datetime64[ns]', freq=None)\n",
      "DatetimeIndex(['2020-04-29'], dtype='datetime64[ns]', freq=None)\n",
      "DatetimeIndex(['2020-04-29'], dtype='datetime64[ns]', freq=None)\n",
      "DatetimeIndex(['2020-04-29'], dtype='datetime64[ns]', freq=None)\n",
      "DatetimeIndex(['2020-04-29'], dtype='datetime64[ns]', freq=None)\n",
      "DatetimeIndex(['2020-04-29'], dtype='datetime64[ns]', freq=None)\n",
      "DatetimeIndex(['2020-04-29'], dtype='datetime64[ns]', freq=None)\n",
      "DatetimeIndex(['2020-04-29'], dtype='datetime64[ns]', freq=None)\n",
      "DatetimeIndex(['2020-04-29'], dtype='datetime64[ns]', freq=None)\n",
      "DatetimeIndex(['2020-04-29'], dtype='datetime64[ns]', freq=None)\n",
      "DatetimeIndex(['2020-04-29'], dtype='datetime64[ns]', freq=None)\n",
      "DatetimeIndex(['2020-04-29'], dtype='datetime64[ns]', freq=None)\n",
      "DatetimeIndex(['2020-04-29'], dtype='datetime64[ns]', freq=None)\n",
      "DatetimeIndex(['2020-04-29'], dtype='datetime64[ns]', freq=None)\n",
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      "DatetimeIndex(['2020-04-15'], dtype='datetime64[ns]', freq=None)\n",
      "DatetimeIndex(['2020-04-15'], dtype='datetime64[ns]', freq=None)\n",
      "DatetimeIndex(['2020-04-15'], dtype='datetime64[ns]', freq=None)\n",
      "DatetimeIndex(['2020-04-15'], dtype='datetime64[ns]', freq=None)\n",
      "DatetimeIndex(['2020-04-15'], dtype='datetime64[ns]', freq=None)\n",
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      "DatetimeIndex(['2020-04-15'], dtype='datetime64[ns]', freq=None)\n",
      "DatetimeIndex(['2020-04-15'], dtype='datetime64[ns]', freq=None)\n",
      "DatetimeIndex(['2020-04-15'], dtype='datetime64[ns]', freq=None)\n",
      "DatetimeIndex(['2020-04-15'], dtype='datetime64[ns]', freq=None)\n",
      "DatetimeIndex(['2020-04-15'], dtype='datetime64[ns]', freq=None)\n",
      "DatetimeIndex(['2020-04-15'], dtype='datetime64[ns]', freq=None)\n",
      "DatetimeIndex(['2020-04-15'], dtype='datetime64[ns]', freq=None)\n",
      "DatetimeIndex(['2020-04-15'], dtype='datetime64[ns]', freq=None)\n",
      "DatetimeIndex(['2020-04-15'], dtype='datetime64[ns]', freq=None)\n",
      "DatetimeIndex(['2020-04-15'], dtype='datetime64[ns]', freq=None)\n",
      "DatetimeIndex(['2020-04-15'], dtype='datetime64[ns]', freq=None)\n",
      "DatetimeIndex(['2020-04-15'], dtype='datetime64[ns]', freq=None)\n",
      "DatetimeIndex(['2020-04-15'], dtype='datetime64[ns]', freq=None)\n",
      "DatetimeIndex(['2020-04-15'], dtype='datetime64[ns]', freq=None)\n",
      "DatetimeIndex(['2020-04-15'], dtype='datetime64[ns]', freq=None)\n",
      "DatetimeIndex(['2020-04-15'], dtype='datetime64[ns]', freq=None)\n",
      "DatetimeIndex(['2020-04-15'], dtype='datetime64[ns]', freq=None)\n",
      "DatetimeIndex(['2020-04-15'], dtype='datetime64[ns]', freq=None)\n",
      "DatetimeIndex(['2020-04-15'], dtype='datetime64[ns]', freq=None)\n",
      "DatetimeIndex(['2020-04-15'], dtype='datetime64[ns]', freq=None)\n",
      "DatetimeIndex(['2020-04-15'], dtype='datetime64[ns]', freq=None)\n",
      "DatetimeIndex(['2020-04-15'], dtype='datetime64[ns]', freq=None)\n",
      "DatetimeIndex(['2020-04-15'], dtype='datetime64[ns]', freq=None)\n",
      "DatetimeIndex(['2020-04-15'], dtype='datetime64[ns]', freq=None)\n",
      "DatetimeIndex(['2020-04-15'], dtype='datetime64[ns]', freq=None)\n",
      "DatetimeIndex(['2020-04-15'], dtype='datetime64[ns]', freq=None)\n",
      "DatetimeIndex(['2020-04-15'], dtype='datetime64[ns]', freq=None)\n",
      "DatetimeIndex(['2020-04-15'], dtype='datetime64[ns]', freq=None)\n",
      "DatetimeIndex(['2020-04-15'], dtype='datetime64[ns]', freq=None)\n",
      "DatetimeIndex(['2020-04-15'], dtype='datetime64[ns]', freq=None)\n",
      "DatetimeIndex(['2020-04-15'], dtype='datetime64[ns]', freq=None)\n",
      "DatetimeIndex(['2020-04-15'], dtype='datetime64[ns]', freq=None)\n",
      "DatetimeIndex(['2020-04-15'], dtype='datetime64[ns]', freq=None)\n",
      "DatetimeIndex(['2020-04-15'], dtype='datetime64[ns]', freq=None)\n",
      "DatetimeIndex(['2020-04-15'], dtype='datetime64[ns]', freq=None)\n",
      "DatetimeIndex(['2020-04-15'], dtype='datetime64[ns]', freq=None)\n",
      "DatetimeIndex(['2020-04-15'], dtype='datetime64[ns]', freq=None)\n",
      "DatetimeIndex(['2020-04-15'], dtype='datetime64[ns]', freq=None)\n",
      "DatetimeIndex(['2020-04-15'], dtype='datetime64[ns]', freq=None)\n",
      "DatetimeIndex(['2020-04-15'], dtype='datetime64[ns]', freq=None)\n",
      "DatetimeIndex(['2020-04-15'], dtype='datetime64[ns]', freq=None)\n",
      "DatetimeIndex(['2020-04-15'], dtype='datetime64[ns]', freq=None)\n",
      "DatetimeIndex(['2020-04-15'], dtype='datetime64[ns]', freq=None)\n",
      "DatetimeIndex(['2020-04-15'], dtype='datetime64[ns]', freq=None)\n",
      "DatetimeIndex(['2020-04-15'], dtype='datetime64[ns]', freq=None)\n",
      "DatetimeIndex(['2020-04-15'], dtype='datetime64[ns]', freq=None)\n",
      "DatetimeIndex(['2020-04-15'], dtype='datetime64[ns]', freq=None)\n",
      "DatetimeIndex(['2020-04-15'], dtype='datetime64[ns]', freq=None)\n",
      "DatetimeIndex(['2020-04-15'], dtype='datetime64[ns]', freq=None)\n",
      "DatetimeIndex(['2020-04-15'], dtype='datetime64[ns]', freq=None)\n",
      "DatetimeIndex(['2020-04-15'], dtype='datetime64[ns]', freq=None)\n",
      "DatetimeIndex(['2020-04-15'], dtype='datetime64[ns]', freq=None)\n",
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      "DatetimeIndex(['2020-04-15'], dtype='datetime64[ns]', freq=None)\n",
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      "DatetimeIndex(['2020-04-28'], dtype='datetime64[ns]', freq=None)\n",
      "DatetimeIndex(['2020-04-28'], dtype='datetime64[ns]', freq=None)\n",
      "DatetimeIndex(['2020-04-28'], dtype='datetime64[ns]', freq=None)\n",
      "DatetimeIndex(['2020-04-28'], dtype='datetime64[ns]', freq=None)\n",
      "DatetimeIndex(['2020-04-28'], dtype='datetime64[ns]', freq=None)\n",
      "DatetimeIndex(['2020-04-28'], dtype='datetime64[ns]', freq=None)\n",
      "DatetimeIndex(['2020-04-28'], dtype='datetime64[ns]', freq=None)\n",
      "DatetimeIndex(['2020-04-28'], dtype='datetime64[ns]', freq=None)\n",
      "DatetimeIndex(['2020-04-28'], dtype='datetime64[ns]', freq=None)\n",
      "DatetimeIndex(['2020-04-28'], dtype='datetime64[ns]', freq=None)\n",
      "DatetimeIndex(['2020-04-28'], dtype='datetime64[ns]', freq=None)\n",
      "DatetimeIndex(['2020-04-28'], dtype='datetime64[ns]', freq=None)\n",
      "DatetimeIndex(['2020-04-28'], dtype='datetime64[ns]', freq=None)\n",
      "DatetimeIndex(['2020-04-28'], dtype='datetime64[ns]', freq=None)\n",
      "DatetimeIndex(['2020-04-28'], dtype='datetime64[ns]', freq=None)\n",
      "DatetimeIndex(['2020-04-28'], dtype='datetime64[ns]', freq=None)\n",
      "DatetimeIndex(['2020-04-28'], dtype='datetime64[ns]', freq=None)\n",
      "DatetimeIndex(['2020-04-28'], dtype='datetime64[ns]', freq=None)\n",
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      "DatetimeIndex(['2020-04-29'], dtype='datetime64[ns]', freq=None)\n",
      "DatetimeIndex(['2020-04-29'], dtype='datetime64[ns]', freq=None)\n",
      "DatetimeIndex(['2020-04-29'], dtype='datetime64[ns]', freq=None)\n",
      "DatetimeIndex(['2020-04-29'], dtype='datetime64[ns]', freq=None)\n",
      "DatetimeIndex(['2020-04-29'], dtype='datetime64[ns]', freq=None)\n",
      "DatetimeIndex(['2020-04-29'], dtype='datetime64[ns]', freq=None)\n",
      "DatetimeIndex(['2020-04-29'], dtype='datetime64[ns]', freq=None)\n",
      "DatetimeIndex(['2020-04-29'], dtype='datetime64[ns]', freq=None)\n",
      "DatetimeIndex(['2020-04-29'], dtype='datetime64[ns]', freq=None)\n",
      "DatetimeIndex(['2020-04-29'], dtype='datetime64[ns]', freq=None)\n",
      "DatetimeIndex(['2020-04-29'], dtype='datetime64[ns]', freq=None)\n",
      "DatetimeIndex(['2020-04-29'], dtype='datetime64[ns]', freq=None)\n",
      "DatetimeIndex(['2020-04-29'], dtype='datetime64[ns]', freq=None)\n",
      "DatetimeIndex(['2020-04-29'], dtype='datetime64[ns]', freq=None)\n",
      "DatetimeIndex(['2020-04-29'], dtype='datetime64[ns]', freq=None)\n",
      "DatetimeIndex(['2020-04-29'], dtype='datetime64[ns]', freq=None)\n",
      "DatetimeIndex(['2020-04-29'], dtype='datetime64[ns]', freq=None)\n",
      "DatetimeIndex(['2020-04-29'], dtype='datetime64[ns]', freq=None)\n",
      "DatetimeIndex(['2020-04-29'], dtype='datetime64[ns]', freq=None)\n",
      "DatetimeIndex(['2020-04-29'], dtype='datetime64[ns]', freq=None)\n",
      "DatetimeIndex(['2020-04-29'], dtype='datetime64[ns]', freq=None)\n",
      "DatetimeIndex(['2020-04-29'], dtype='datetime64[ns]', freq=None)\n",
      "DatetimeIndex(['2020-04-29'], dtype='datetime64[ns]', freq=None)\n",
      "DatetimeIndex(['2020-04-29'], dtype='datetime64[ns]', freq=None)\n",
      "DatetimeIndex(['2020-04-29'], dtype='datetime64[ns]', freq=None)\n",
      "DatetimeIndex(['2020-04-29'], dtype='datetime64[ns]', freq=None)\n",
      "DatetimeIndex(['2020-04-29'], dtype='datetime64[ns]', freq=None)\n",
      "DatetimeIndex(['2020-04-29'], dtype='datetime64[ns]', freq=None)\n",
      "DatetimeIndex(['2020-04-29'], dtype='datetime64[ns]', freq=None)\n",
      "DatetimeIndex(['2020-04-29'], dtype='datetime64[ns]', freq=None)\n",
      "DatetimeIndex(['2020-04-29'], dtype='datetime64[ns]', freq=None)\n",
      "DatetimeIndex(['2020-04-29'], dtype='datetime64[ns]', freq=None)\n",
      "DatetimeIndex(['2020-04-29'], dtype='datetime64[ns]', freq=None)\n",
      "DatetimeIndex(['2020-04-29'], dtype='datetime64[ns]', freq=None)\n",
      "DatetimeIndex(['2020-04-29'], dtype='datetime64[ns]', freq=None)\n",
      "DatetimeIndex(['2020-04-29'], dtype='datetime64[ns]', freq=None)\n",
      "DatetimeIndex(['2020-04-29'], dtype='datetime64[ns]', freq=None)\n",
      "DatetimeIndex(['2020-04-29'], dtype='datetime64[ns]', freq=None)\n",
      "DatetimeIndex(['2020-04-29'], dtype='datetime64[ns]', freq=None)\n",
      "DatetimeIndex(['2020-04-29'], dtype='datetime64[ns]', freq=None)\n",
      "DatetimeIndex(['2020-04-29'], dtype='datetime64[ns]', freq=None)\n",
      "DatetimeIndex(['2020-04-29'], dtype='datetime64[ns]', freq=None)\n",
      "DatetimeIndex(['2020-04-29'], dtype='datetime64[ns]', freq=None)\n",
      "DatetimeIndex(['2020-04-29'], dtype='datetime64[ns]', freq=None)\n",
      "DatetimeIndex(['2020-04-29'], dtype='datetime64[ns]', freq=None)\n",
      "DatetimeIndex(['2020-04-29'], dtype='datetime64[ns]', freq=None)\n",
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      "DatetimeIndex(['2020-04-10'], dtype='datetime64[ns]', freq=None)\n"
     ]
    }
   ],
   "source": [
    "from datetime import datetime, timedelta\n",
    "county_dic={}\n",
    "for fip in dic_start_date.keys():    \n",
    " county_dic.setdefault(fip, [])\n",
    " county=risk.loc[risk['fips']==fip]    # get only fips with mask recommended \n",
    " county_recomm_date=pd.to_datetime(dic_start_date[fip])\n",
    " n_days_ago =pd.to_datetime(county_recomm_date - timedelta(days=7))  #the calender date one week before mask recommended \n",
    " #Low risk 5/13\n",
    " #mid \n",
    " county=county[(county['date']<=county_recomm_date.values[0])&(county['date']>=n_days_ago.values[0])]\n",
    " #county=county[(county['date']<=\"2020-11-6\")&(county['date']>=\"2020-11-1\")]\n",
    "# county=county[(county['date']<=\"2020-7-19\")&(county['date']>=\"2020-6-10\")]\n",
    "\n",
    " print (county_recomm_date) \n",
    " risk_level=county[\"cdcTransmissionLevel\"].mean()     # CDC risk level mean and consider it\n",
    " #risk_level=county[\"riskLevels.overall\"].mean()     # risk level mean and consider it\n",
    " county_dic[fip].append(risk_level)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {
    "executionInfo": {
     "elapsed": 154,
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     "timestamp": 1674675787289,
     "user": {
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      "userId": "17271150753343271230"
     },
     "user_tz": 300
    },
    "id": "7cfbec1c"
   },
   "outputs": [],
   "source": [
    "recomm_risk=pd.DataFrame.from_dict(county_dic)\n",
    "recomm_risk = recomm_risk.T\n",
    "df_recomm_risk=pd.DataFrame(recomm_risk)\n",
    "\n",
    "df_recomm_risk=df_recomm_risk.reset_index()\n",
    "df_recomm_risk.columns = ['fips','risk']"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
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       "      fips  risk\n",
       "0     2013   NaN\n",
       "1     2068   NaN\n",
       "2     2090  1.00\n",
       "3     2100  0.00\n",
       "4     2122  0.00\n",
       "..     ...   ...\n",
       "533  49049  1.00\n",
       "534  49051  2.75\n",
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       "536  49055   NaN\n",
       "537  49057  1.00\n",
       "\n",
       "[538 rows x 2 columns]"
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     },
     "execution_count": 18,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_recomm_risk"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "metadata": {
    "executionInfo": {
     "elapsed": 130,
     "status": "ok",
     "timestamp": 1674676275167,
     "user": {
      "displayName": "Amera Al-Amery",
      "userId": "17271150753343271230"
     },
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    },
    "id": "f2b75834"
   },
   "outputs": [],
   "source": [
    "# ALL EXCEPT EXTREME df_recomm_risk.to_csv(\"C:/Users/nimda/Desktop/Research_2/Data/New_Data/recommended_only_risk_counties_risk.csv\")\n",
    "df_recomm_risk.to_csv(\"/content/drive/MyDrive/Colab Notebooks/Mask_Project/recommended_risk_levels_according_county_date.csv\")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "a16831d1"
   },
   "source": [
    "# Bring the level for each county before its indoor exact date ( The switching date)\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/"
    },
    "executionInfo": {
     "elapsed": 260,
     "status": "ok",
     "timestamp": 1674677656574,
     "user": {
      "displayName": "Amera Al-Amery",
      "userId": "17271150753343271230"
     },
     "user_tz": 300
    },
    "id": "f0cdb8e4",
    "outputId": "cee7eb55-8764-4208-b96e-961b78155aea"
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   "outputs": [
    {
     "data": {
      "text/plain": [
       "2998"
      ]
     },
     "execution_count": 26,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#indoor_start_date=pd.read_csv(\"C:/Users/nimda/Desktop/Research_2/Data/New_Data/indoor_start_date.csv\")\n",
    "mask_start_date=pd.read_csv(\"/content/drive/MyDrive/Colab Notebooks/Mask_Project/categories_final.csv\") # category datset\n",
    "# remove N cat which do not have any category\n",
    "mask_start_date2=mask_start_date[mask_start_date['Category']!=\"N\"]\n",
    "length=len(mask_start_date2)\n",
    "length"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "metadata": {
    "executionInfo": {
     "elapsed": 748,
     "status": "ok",
     "timestamp": 1674676174724,
     "user": {
      "displayName": "Amera Al-Amery",
      "userId": "17271150753343271230"
     },
     "user_tz": 300
    },
    "id": "f362126b"
   },
   "outputs": [],
   "source": [
    "\n",
    "#keep conties which implemented mask \n",
    "#pick the min date eralist by replacing 1/1/1900 \n",
    "#mask_start_date['Date']=mask_start_date['Date'].replace(\"1900-01-01\",\"2050-01-01\")\n",
    "\n",
    "\n",
    "dic_start_date={}\n",
    "for i in range((length)):\n",
    "\n",
    "    date=mask_start_date2.iloc[i]['Date']\n",
    "   \n",
    "    fips= mask_start_date2.iloc[i]['fips']\n",
    "    dic_start_date.setdefault(fips, [])\n",
    "\n",
    "   # final_date=pd.to_datetime(final_date)\n",
    "\n",
    "    \n",
    "    dic_start_date[fips].append(date)\n",
    "\n",
    "    "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "id": "d731a653"
   },
   "outputs": [],
   "source": [
    "#dic_start_date = dict( [(k,v) for k,v in dic_start_date2.items() if len(v)>0])\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/"
    },
    "executionInfo": {
     "elapsed": 8999,
     "status": "ok",
     "timestamp": 1674676212569,
     "user": {
      "displayName": "Amera Al-Amery",
      "userId": "17271150753343271230"
     },
     "user_tz": 300
    },
    "id": "b953e40f",
    "outputId": "db091867-f7b8-4c3d-fffa-21e3381d47d0"
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "2223965"
      ]
     },
     "execution_count": 21,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "from datetime import datetime, timedelta\n",
    "\n",
    "risk = pd.read_csv(\"/content/drive/MyDrive/Colab Notebooks/Mask_Project/counties.timeseries.csv\")\n",
    "length=len(risk)\n",
    "length"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/"
    },
    "executionInfo": {
     "elapsed": 26096,
     "status": "ok",
     "timestamp": 1674676251215,
     "user": {
      "displayName": "Amera Al-Amery",
      "userId": "17271150753343271230"
     },
     "user_tz": 300
    },
    "id": "7ffa4da4",
    "outputId": "2ed4aeca-4732-453c-8f73-30319b278599"
   },
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "<ipython-input-22-83848177b99e>:5: SettingWithCopyWarning: \n",
      "A value is trying to be set on a copy of a slice from a DataFrame.\n",
      "Try using .loc[row_indexer,col_indexer] = value instead\n",
      "\n",
      "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
      "  county['date']=pd.to_datetime(county['date'])\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "1001 DatetimeIndex(['2020-07-16'], dtype='datetime64[ns]', freq=None)\n",
      "1003 DatetimeIndex(['2020-07-16'], dtype='datetime64[ns]', freq=None)\n",
      "1005 DatetimeIndex(['2020-07-16'], dtype='datetime64[ns]', freq=None)\n",
      "1007 DatetimeIndex(['2020-07-16'], dtype='datetime64[ns]', freq=None)\n",
      "1009 DatetimeIndex(['2020-07-16'], dtype='datetime64[ns]', freq=None)\n",
      "1011 DatetimeIndex(['2020-07-16'], dtype='datetime64[ns]', freq=None)\n",
      "1013 DatetimeIndex(['2020-07-16'], dtype='datetime64[ns]', freq=None)\n",
      "1015 DatetimeIndex(['2020-07-16'], dtype='datetime64[ns]', freq=None)\n",
      "1017 DatetimeIndex(['2020-07-16'], dtype='datetime64[ns]', freq=None)\n",
      "1019 DatetimeIndex(['2020-07-16'], dtype='datetime64[ns]', freq=None)\n",
      "1021 DatetimeIndex(['2020-07-16'], dtype='datetime64[ns]', freq=None)\n",
      "1023 DatetimeIndex(['2020-07-16'], dtype='datetime64[ns]', freq=None)\n",
      "1025 DatetimeIndex(['2020-07-16'], dtype='datetime64[ns]', freq=None)\n",
      "1027 DatetimeIndex(['2020-07-16'], dtype='datetime64[ns]', freq=None)\n",
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      "1031 DatetimeIndex(['2020-07-16'], dtype='datetime64[ns]', freq=None)\n",
      "1033 DatetimeIndex(['2020-07-16'], dtype='datetime64[ns]', freq=None)\n",
      "1035 DatetimeIndex(['2020-07-16'], dtype='datetime64[ns]', freq=None)\n",
      "1037 DatetimeIndex(['2020-07-16'], dtype='datetime64[ns]', freq=None)\n",
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      "8029 DatetimeIndex(['2020-07-16'], dtype='datetime64[ns]', freq=None)\n",
      "8031 DatetimeIndex(['2020-05-06'], dtype='datetime64[ns]', freq=None)\n",
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      "13291 DatetimeIndex(['2020-05-01'], dtype='datetime64[ns]', freq=None)\n",
      "13293 DatetimeIndex(['2020-05-01'], dtype='datetime64[ns]', freq=None)\n",
      "13295 DatetimeIndex(['2020-05-01'], dtype='datetime64[ns]', freq=None)\n",
      "13297 DatetimeIndex(['2020-05-01'], dtype='datetime64[ns]', freq=None)\n",
      "13299 DatetimeIndex(['2020-05-01'], dtype='datetime64[ns]', freq=None)\n",
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      "21199 DatetimeIndex(['2020-06-30'], dtype='datetime64[ns]', freq=None)\n",
      "21201 DatetimeIndex(['2020-06-30'], dtype='datetime64[ns]', freq=None)\n",
      "21203 DatetimeIndex(['2020-06-30'], dtype='datetime64[ns]', freq=None)\n",
      "21207 DatetimeIndex(['2020-06-30'], dtype='datetime64[ns]', freq=None)\n",
      "21209 DatetimeIndex(['2020-06-30'], dtype='datetime64[ns]', freq=None)\n",
      "21211 DatetimeIndex(['2020-06-30'], dtype='datetime64[ns]', freq=None)\n",
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      "27161 DatetimeIndex(['2020-07-25'], dtype='datetime64[ns]', freq=None)\n",
      "27163 DatetimeIndex(['2020-07-25'], dtype='datetime64[ns]', freq=None)\n",
      "27165 DatetimeIndex(['2020-07-25'], dtype='datetime64[ns]', freq=None)\n",
      "27167 DatetimeIndex(['2020-07-25'], dtype='datetime64[ns]', freq=None)\n",
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      "31123 DatetimeIndex(['2020-11-11'], dtype='datetime64[ns]', freq=None)\n",
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      "51640 DatetimeIndex(['2020-05-29'], dtype='datetime64[ns]', freq=None)\n",
      "51650 DatetimeIndex(['2020-05-29'], dtype='datetime64[ns]', freq=None)\n",
      "51660 DatetimeIndex(['2020-05-29'], dtype='datetime64[ns]', freq=None)\n",
      "51670 DatetimeIndex(['2020-05-29'], dtype='datetime64[ns]', freq=None)\n",
      "51678 DatetimeIndex(['2020-05-29'], dtype='datetime64[ns]', freq=None)\n",
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      "51683 DatetimeIndex(['2020-05-29'], dtype='datetime64[ns]', freq=None)\n",
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      "45067 DatetimeIndex(['2020-08-03'], dtype='datetime64[ns]', freq=None)\n",
      "45069 DatetimeIndex(['2020-08-03'], dtype='datetime64[ns]', freq=None)\n",
      "45071 DatetimeIndex(['2020-07-01'], dtype='datetime64[ns]', freq=None)\n",
      "45073 DatetimeIndex(['2020-08-03'], dtype='datetime64[ns]', freq=None)\n",
      "45075 DatetimeIndex(['2020-07-03'], dtype='datetime64[ns]', freq=None)\n",
      "45077 DatetimeIndex(['2020-08-03'], dtype='datetime64[ns]', freq=None)\n",
      "45079 DatetimeIndex(['2020-06-26'], dtype='datetime64[ns]', freq=None)\n",
      "45081 DatetimeIndex(['2020-08-03'], dtype='datetime64[ns]', freq=None)\n",
      "45083 DatetimeIndex(['2020-08-03'], dtype='datetime64[ns]', freq=None)\n",
      "45085 DatetimeIndex(['2020-07-03'], dtype='datetime64[ns]', freq=None)\n",
      "45087 DatetimeIndex(['2020-08-03'], dtype='datetime64[ns]', freq=None)\n",
      "45089 DatetimeIndex(['2020-07-13'], dtype='datetime64[ns]', freq=None)\n",
      "45091 DatetimeIndex(['2020-07-10'], dtype='datetime64[ns]', freq=None)\n",
      "46027 DatetimeIndex(['2020-07-15', '2020-07-15'], dtype='datetime64[ns]', freq=None)\n",
      "46083 DatetimeIndex(['2020-11-21'], dtype='datetime64[ns]', freq=None)\n",
      "46099 DatetimeIndex(['2020-11-21'], dtype='datetime64[ns]', freq=None)\n",
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      "48003 DatetimeIndex(['2020-07-03'], dtype='datetime64[ns]', freq=None)\n",
      "48005 DatetimeIndex(['2020-07-03'], dtype='datetime64[ns]', freq=None)\n",
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      "48009 DatetimeIndex(['2020-10-26'], dtype='datetime64[ns]', freq=None)\n",
      "48013 DatetimeIndex(['2020-07-03'], dtype='datetime64[ns]', freq=None)\n",
      "48015 DatetimeIndex(['2020-07-03'], dtype='datetime64[ns]', freq=None)\n",
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      "48021 DatetimeIndex(['2020-07-03'], dtype='datetime64[ns]', freq=None)\n",
      "48025 DatetimeIndex(['2020-07-03'], dtype='datetime64[ns]', freq=None)\n",
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      "48035 DatetimeIndex(['2020-07-03'], dtype='datetime64[ns]', freq=None)\n",
      "48037 DatetimeIndex(['2020-07-03'], dtype='datetime64[ns]', freq=None)\n",
      "48039 DatetimeIndex(['2020-07-03'], dtype='datetime64[ns]', freq=None)\n",
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      "48049 DatetimeIndex(['2020-07-03'], dtype='datetime64[ns]', freq=None)\n",
      "48051 DatetimeIndex(['2020-07-03'], dtype='datetime64[ns]', freq=None)\n",
      "48053 DatetimeIndex(['2020-07-03'], dtype='datetime64[ns]', freq=None)\n",
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      "48093 DatetimeIndex(['2020-07-03'], dtype='datetime64[ns]', freq=None)\n",
      "48095 DatetimeIndex(['2020-07-03'], dtype='datetime64[ns]', freq=None)\n",
      "48097 DatetimeIndex(['2020-07-03'], dtype='datetime64[ns]', freq=None)\n",
      "48099 DatetimeIndex(['2020-07-03'], dtype='datetime64[ns]', freq=None)\n",
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      "48109 DatetimeIndex(['2020-07-03'], dtype='datetime64[ns]', freq=None)\n",
      "48111 DatetimeIndex(['2020-07-03'], dtype='datetime64[ns]', freq=None)\n",
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      "48117 DatetimeIndex(['2020-07-03'], dtype='datetime64[ns]', freq=None)\n",
      "48121 DatetimeIndex(['2020-07-03'], dtype='datetime64[ns]', freq=None)\n",
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      "48195 DatetimeIndex(['2020-10-02'], dtype='datetime64[ns]', freq=None)\n",
      "48205 DatetimeIndex(['2020-10-24'], dtype='datetime64[ns]', freq=None)\n",
      "48239 DatetimeIndex(['2020-07-03'], dtype='datetime64[ns]', freq=None)\n",
      "48253 DatetimeIndex(['2020-10-16'], dtype='datetime64[ns]', freq=None)\n",
      "48255 DatetimeIndex(['2020-07-03'], dtype='datetime64[ns]', freq=None)\n",
      "48265 DatetimeIndex(['2020-10-02'], dtype='datetime64[ns]', freq=None)\n",
      "48299 DatetimeIndex(['2020-09-30'], dtype='datetime64[ns]', freq=None)\n",
      "48337 DatetimeIndex(['2020-10-17'], dtype='datetime64[ns]', freq=None)\n",
      "48365 DatetimeIndex(['2020-09-04'], dtype='datetime64[ns]', freq=None)\n",
      "48383 DatetimeIndex(['2020-07-03'], dtype='datetime64[ns]', freq=None)\n",
      "48385 DatetimeIndex(['2020-09-09', '2020-09-09'], dtype='datetime64[ns]', freq=None)\n",
      "48429 DatetimeIndex(['2020-10-03'], dtype='datetime64[ns]', freq=None)\n",
      "48435 DatetimeIndex(['2020-11-10'], dtype='datetime64[ns]', freq=None)\n",
      "48463 DatetimeIndex(['2020-07-03'], dtype='datetime64[ns]', freq=None)\n",
      "48475 DatetimeIndex(['2020-11-13'], dtype='datetime64[ns]', freq=None)\n",
      "30051 DatetimeIndex(['NaT'], dtype='datetime64[ns]', freq=None)\n",
      "48029 DatetimeIndex(['2020-06-18'], dtype='datetime64[ns]', freq=None)\n",
      "10001 DatetimeIndex(['2020-04-28'], dtype='datetime64[ns]', freq=None)\n",
      "15003 DatetimeIndex(['2020-04-26'], dtype='datetime64[ns]', freq=None)\n",
      "15007 DatetimeIndex(['2020-04-26'], dtype='datetime64[ns]', freq=None)\n",
      "15009 DatetimeIndex(['2020-04-26'], dtype='datetime64[ns]', freq=None)\n",
      "23001 DatetimeIndex(['2020-05-01'], dtype='datetime64[ns]', freq=None)\n",
      "23003 DatetimeIndex(['2020-05-01'], dtype='datetime64[ns]', freq=None)\n",
      "23005 DatetimeIndex(['2020-05-01'], dtype='datetime64[ns]', freq=None)\n",
      "23007 DatetimeIndex(['2020-05-01'], dtype='datetime64[ns]', freq=None)\n",
      "23009 DatetimeIndex(['2020-05-01'], dtype='datetime64[ns]', freq=None)\n",
      "23011 DatetimeIndex(['2020-05-01'], dtype='datetime64[ns]', freq=None)\n",
      "23013 DatetimeIndex(['2020-05-01'], dtype='datetime64[ns]', freq=None)\n",
      "23015 DatetimeIndex(['2020-05-01'], dtype='datetime64[ns]', freq=None)\n",
      "23017 DatetimeIndex(['2020-05-01'], dtype='datetime64[ns]', freq=None)\n",
      "23019 DatetimeIndex(['2020-05-01'], dtype='datetime64[ns]', freq=None)\n",
      "23021 DatetimeIndex(['2020-05-01'], dtype='datetime64[ns]', freq=None)\n",
      "23023 DatetimeIndex(['2020-05-01'], dtype='datetime64[ns]', freq=None)\n",
      "23025 DatetimeIndex(['2020-05-01'], dtype='datetime64[ns]', freq=None)\n",
      "23027 DatetimeIndex(['2020-05-01'], dtype='datetime64[ns]', freq=None)\n",
      "23029 DatetimeIndex(['2020-05-01'], dtype='datetime64[ns]', freq=None)\n",
      "23031 DatetimeIndex(['2020-05-01'], dtype='datetime64[ns]', freq=None)\n",
      "24001 DatetimeIndex(['2020-04-18'], dtype='datetime64[ns]', freq=None)\n",
      "24003 DatetimeIndex(['2020-04-15'], dtype='datetime64[ns]', freq=None)\n",
      "24005 DatetimeIndex(['2020-04-18'], dtype='datetime64[ns]', freq=None)\n",
      "24009 DatetimeIndex(['2020-04-18'], dtype='datetime64[ns]', freq=None)\n",
      "24011 DatetimeIndex(['2020-04-18'], dtype='datetime64[ns]', freq=None)\n",
      "24013 DatetimeIndex(['2020-04-18'], dtype='datetime64[ns]', freq=None)\n",
      "24015 DatetimeIndex(['2020-04-18'], dtype='datetime64[ns]', freq=None)\n",
      "24017 DatetimeIndex(['2020-04-15'], dtype='datetime64[ns]', freq=None)\n",
      "24019 DatetimeIndex(['2020-04-18'], dtype='datetime64[ns]', freq=None)\n",
      "24021 DatetimeIndex(['2020-04-16'], dtype='datetime64[ns]', freq=None)\n",
      "24025 DatetimeIndex(['2020-04-18'], dtype='datetime64[ns]', freq=None)\n",
      "24031 DatetimeIndex(['2020-04-13'], dtype='datetime64[ns]', freq=None)\n",
      "24033 DatetimeIndex(['2020-04-15'], dtype='datetime64[ns]', freq=None)\n",
      "24035 DatetimeIndex(['2020-04-18'], dtype='datetime64[ns]', freq=None)\n",
      "24037 DatetimeIndex(['2020-04-18'], dtype='datetime64[ns]', freq=None)\n",
      "24039 DatetimeIndex(['2020-04-18'], dtype='datetime64[ns]', freq=None)\n",
      "24041 DatetimeIndex(['2020-04-18'], dtype='datetime64[ns]', freq=None)\n",
      "24043 DatetimeIndex(['2020-04-18'], dtype='datetime64[ns]', freq=None)\n",
      "24045 DatetimeIndex(['2020-04-18'], dtype='datetime64[ns]', freq=None)\n",
      "24047 DatetimeIndex(['2020-04-18'], dtype='datetime64[ns]', freq=None)\n",
      "34001 DatetimeIndex(['2020-04-10'], dtype='datetime64[ns]', freq=None)\n",
      "34003 DatetimeIndex(['2020-04-10'], dtype='datetime64[ns]', freq=None)\n",
      "34005 DatetimeIndex(['2020-04-10'], dtype='datetime64[ns]', freq=None)\n",
      "34007 DatetimeIndex(['2020-04-10'], dtype='datetime64[ns]', freq=None)\n",
      "34009 DatetimeIndex(['2020-04-10'], dtype='datetime64[ns]', freq=None)\n",
      "34011 DatetimeIndex(['2020-04-10'], dtype='datetime64[ns]', freq=None)\n",
      "34013 DatetimeIndex(['2020-04-10'], dtype='datetime64[ns]', freq=None)\n",
      "34015 DatetimeIndex(['2020-04-10'], dtype='datetime64[ns]', freq=None)\n",
      "34017 DatetimeIndex(['2020-04-10'], dtype='datetime64[ns]', freq=None)\n",
      "34019 DatetimeIndex(['2020-04-10'], dtype='datetime64[ns]', freq=None)\n",
      "34021 DatetimeIndex(['2020-04-10'], dtype='datetime64[ns]', freq=None)\n",
      "34023 DatetimeIndex(['2020-04-10'], dtype='datetime64[ns]', freq=None)\n",
      "34025 DatetimeIndex(['2020-04-10'], dtype='datetime64[ns]', freq=None)\n",
      "34027 DatetimeIndex(['2020-04-10'], dtype='datetime64[ns]', freq=None)\n",
      "34029 DatetimeIndex(['2020-04-10'], dtype='datetime64[ns]', freq=None)\n",
      "34031 DatetimeIndex(['2020-04-10'], dtype='datetime64[ns]', freq=None)\n",
      "34033 DatetimeIndex(['2020-04-10'], dtype='datetime64[ns]', freq=None)\n",
      "34035 DatetimeIndex(['2020-04-10'], dtype='datetime64[ns]', freq=None)\n",
      "34037 DatetimeIndex(['2020-04-10'], dtype='datetime64[ns]', freq=None)\n",
      "34039 DatetimeIndex(['2020-04-10'], dtype='datetime64[ns]', freq=None)\n",
      "34041 DatetimeIndex(['2020-04-10'], dtype='datetime64[ns]', freq=None)\n",
      "35001 DatetimeIndex(['2020-05-16'], dtype='datetime64[ns]', freq=None)\n",
      "35003 DatetimeIndex(['2020-05-16'], dtype='datetime64[ns]', freq=None)\n",
      "35005 DatetimeIndex(['2020-05-16'], dtype='datetime64[ns]', freq=None)\n",
      "35006 DatetimeIndex(['2020-05-16'], dtype='datetime64[ns]', freq=None)\n",
      "35007 DatetimeIndex(['2020-05-16'], dtype='datetime64[ns]', freq=None)\n",
      "35009 DatetimeIndex(['2020-05-16'], dtype='datetime64[ns]', freq=None)\n",
      "35011 DatetimeIndex(['2020-05-16'], dtype='datetime64[ns]', freq=None)\n",
      "35013 DatetimeIndex(['2020-05-16'], dtype='datetime64[ns]', freq=None)\n",
      "35015 DatetimeIndex(['2020-05-16'], dtype='datetime64[ns]', freq=None)\n",
      "35017 DatetimeIndex(['2020-05-16'], dtype='datetime64[ns]', freq=None)\n",
      "35019 DatetimeIndex(['2020-05-16'], dtype='datetime64[ns]', freq=None)\n",
      "35021 DatetimeIndex(['2020-05-16'], dtype='datetime64[ns]', freq=None)\n",
      "35023 DatetimeIndex(['2020-05-16'], dtype='datetime64[ns]', freq=None)\n",
      "35025 DatetimeIndex(['2020-05-16'], dtype='datetime64[ns]', freq=None)\n",
      "35027 DatetimeIndex(['2020-05-16'], dtype='datetime64[ns]', freq=None)\n",
      "35028 DatetimeIndex(['2020-05-16'], dtype='datetime64[ns]', freq=None)\n",
      "35029 DatetimeIndex(['2020-05-16'], dtype='datetime64[ns]', freq=None)\n",
      "35031 DatetimeIndex(['2020-05-16'], dtype='datetime64[ns]', freq=None)\n",
      "35033 DatetimeIndex(['2020-05-16'], dtype='datetime64[ns]', freq=None)\n",
      "35035 DatetimeIndex(['2020-05-16'], dtype='datetime64[ns]', freq=None)\n",
      "35037 DatetimeIndex(['2020-05-16'], dtype='datetime64[ns]', freq=None)\n",
      "35039 DatetimeIndex(['2020-05-16'], dtype='datetime64[ns]', freq=None)\n",
      "35041 DatetimeIndex(['2020-05-16'], dtype='datetime64[ns]', freq=None)\n",
      "35043 DatetimeIndex(['2020-05-16'], dtype='datetime64[ns]', freq=None)\n",
      "35045 DatetimeIndex(['2020-05-16'], dtype='datetime64[ns]', freq=None)\n",
      "35047 DatetimeIndex(['2020-05-16'], dtype='datetime64[ns]', freq=None)\n",
      "35049 DatetimeIndex(['2020-05-16'], dtype='datetime64[ns]', freq=None)\n",
      "35051 DatetimeIndex(['2020-05-16'], dtype='datetime64[ns]', freq=None)\n",
      "35053 DatetimeIndex(['2020-05-16'], dtype='datetime64[ns]', freq=None)\n",
      "35055 DatetimeIndex(['2020-05-16'], dtype='datetime64[ns]', freq=None)\n",
      "35057 DatetimeIndex(['2020-05-16'], dtype='datetime64[ns]', freq=None)\n",
      "35059 DatetimeIndex(['2020-05-16'], dtype='datetime64[ns]', freq=None)\n",
      "35061 DatetimeIndex(['2020-05-16'], dtype='datetime64[ns]', freq=None)\n",
      "56001 DatetimeIndex(['2020-11-06'], dtype='datetime64[ns]', freq=None)\n",
      "56003 DatetimeIndex(['2020-12-09'], dtype='datetime64[ns]', freq=None)\n",
      "56005 DatetimeIndex(['2020-12-09'], dtype='datetime64[ns]', freq=None)\n",
      "56007 DatetimeIndex(['2020-11-17'], dtype='datetime64[ns]', freq=None)\n",
      "56009 DatetimeIndex(['2020-11-20'], dtype='datetime64[ns]', freq=None)\n",
      "56011 DatetimeIndex(['2020-12-09'], dtype='datetime64[ns]', freq=None)\n",
      "56013 DatetimeIndex(['2020-12-09'], dtype='datetime64[ns]', freq=None)\n",
      "56015 DatetimeIndex(['2020-12-09'], dtype='datetime64[ns]', freq=None)\n",
      "56017 DatetimeIndex(['2020-12-09'], dtype='datetime64[ns]', freq=None)\n",
      "56019 DatetimeIndex(['2020-12-09'], dtype='datetime64[ns]', freq=None)\n",
      "56021 DatetimeIndex(['2020-12-09'], dtype='datetime64[ns]', freq=None)\n",
      "56023 DatetimeIndex(['2020-12-09'], dtype='datetime64[ns]', freq=None)\n",
      "56025 DatetimeIndex(['2020-12-09'], dtype='datetime64[ns]', freq=None)\n",
      "56027 DatetimeIndex(['2020-12-09'], dtype='datetime64[ns]', freq=None)\n",
      "56029 DatetimeIndex(['2020-12-09'], dtype='datetime64[ns]', freq=None)\n",
      "56033 DatetimeIndex(['2020-12-09'], dtype='datetime64[ns]', freq=None)\n",
      "56035 DatetimeIndex(['2020-12-09'], dtype='datetime64[ns]', freq=None)\n",
      "56037 DatetimeIndex(['2020-12-09'], dtype='datetime64[ns]', freq=None)\n",
      "56041 DatetimeIndex(['2020-12-09'], dtype='datetime64[ns]', freq=None)\n",
      "56043 DatetimeIndex(['2020-12-09'], dtype='datetime64[ns]', freq=None)\n",
      "56045 DatetimeIndex(['2020-12-09'], dtype='datetime64[ns]', freq=None)\n"
     ]
    }
   ],
   "source": [
    "county_dic={}\n",
    "for fip in dic_start_date.keys(): \n",
    " county_dic.setdefault(fip, [])\n",
    " county=risk.loc[risk['fips']==fip]\n",
    " county['date']=pd.to_datetime(county['date'])\n",
    " county_indoor_date=pd.to_datetime(dic_start_date[fip])\n",
    " print(fip,county_indoor_date)\n",
    " n_days_ago =pd.to_datetime(county_indoor_date - timedelta(days=7))\n",
    "\n",
    " county=county[(county['date']<=county_indoor_date.values[0])&(county['date']>=n_days_ago.values[0])]\n",
    " #print (county_indoor_date,county) \n",
    " risk_level=county[\"cdcTransmissionLevel\"].mean()\n",
    " county_dic[fip].append(risk_level)\n",
    "\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "metadata": {
    "executionInfo": {
     "elapsed": 136,
     "status": "ok",
     "timestamp": 1674676282266,
     "user": {
      "displayName": "Amera Al-Amery",
      "userId": "17271150753343271230"
     },
     "user_tz": 300
    },
    "id": "36b0d2cb"
   },
   "outputs": [],
   "source": [
    "indoor_risk=pd.DataFrame.from_dict(county_dic)\n",
    "indoor_risk = indoor_risk.T\n",
    "df_indoor_risk=pd.DataFrame(indoor_risk)\n",
    "\n",
    "df_indoor_risk=df_indoor_risk.reset_index()\n",
    "df_indoor_risk.columns = ['fips','risk'] \n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "metadata": {
    "executionInfo": {
     "elapsed": 152,
     "status": "ok",
     "timestamp": 1674676290318,
     "user": {
      "displayName": "Amera Al-Amery",
      "userId": "17271150753343271230"
     },
     "user_tz": 300
    },
    "id": "e7bb51ae"
   },
   "outputs": [],
   "source": [
    "df_indoor_risk.to_csv(\"/content/drive/MyDrive/Colab Notebooks/Mask_Project/risk_levels_new_dates_4_7.csv\")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "cd179141"
   },
   "source": [
    "# End of mask mandate requirements "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "id": "b900289b"
   },
   "outputs": [],
   "source": [
    "df_indoor_risk.to_csv(\"C:/Users/nimda/Desktop/Research_2/Data/New_Data/indoor_risk.csv\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "id": "d2b08533",
    "outputId": "1843b7a0-27a6-46fc-b99d-4f13bff8182a"
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array(['AK', 'AL', 'AR', 'AZ', 'CA', 'CO', 'CT', 'DC', 'DE', 'FL', 'GA',\n",
       "       'HI', 'IA', 'ID', 'IL', 'IN', 'KS', 'KY', 'LA', 'MA', 'MD', 'ME',\n",
       "       'MI', 'MN', 'MO', 'MP', 'MS', 'MT', 'NC', 'ND', 'NE', 'NH', 'NJ',\n",
       "       'NM', 'NV', 'NY', 'OH', 'OK', 'OR', 'PA', 'PR', 'RI', 'SC', 'SD',\n",
       "       'TN', 'TX', 'UT', 'VA', 'VT', 'WA', 'WI', 'WV', 'WY'], dtype=object)"
      ]
     },
     "execution_count": 15,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "np.unique(risk['state'])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "id": "3b56cde1"
   },
   "outputs": [],
   "source": [
    "midwest_abbr = ['ND','SD','NE','KS','MN','IA','MO','WI','IL','IN','MI','OH']\n",
    "\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "id": "2dff809b",
    "outputId": "1c9fd2a8-8398-4d0c-cd03-f92c318468e0"
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array(['IA', 'IL', 'IN', 'KS', 'MI', 'MN', 'MO', 'ND', 'NE', 'OH', 'SD',\n",
       "       'WI'], dtype=object)"
      ]
     },
     "execution_count": 6,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "midwest = risk[risk['state'].isin(['ND','SD','NE','KS','MN','IA','MO','WI','IL','IN','MI','OH'])]\n",
    "np.unique(midwest['state'])\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "id": "0534b608"
   },
   "outputs": [],
   "source": [
    "midwest_INOUT= midwest[midwest['date']>='2020-07-01']\n",
    "midwest_risk_date= midwest_INOUT[midwest_INOUT['date']<='2020-07-15']\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "id": "1883ee9b"
   },
   "outputs": [],
   "source": [
    "midwest_risk_date_clm= midwest_risk_date[['fips', 'riskLevels.overall']]\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "id": "9e0f4b40"
   },
   "outputs": [],
   "source": [
    "risk_level_AVG_July= midwest_risk_date_clm.groupby(['fips']).agg(['mean'])\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "id": "200cdb3e"
   },
   "outputs": [],
   "source": [
    "risk_level_AVG_July.to_csv(\"C:/Users/nimda/Desktop/Research_2/Data/New_Data/us_risk_level_1-15_7.csv\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "id": "073b3671",
    "outputId": "7a71eb1f-53bb-4445-80d1-71443c3e8045"
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array(['AK', 'AZ', 'CA', 'CO', 'HI', 'ID', 'MT', 'NM', 'NV', 'OR', 'UT',\n",
       "       'WA', 'WY'], dtype=object)"
      ]
     },
     "execution_count": 30,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#west \n",
    "west_abbr = [\"AK\", \"AZ\", \"CA\" ,\"CO\" ,\"HI\" ,\"ID\" ,\"MT\" ,\"NM\", \"NV\" ,\"OR\" ,\"UT\" ,\"WA\", \"WY\"]\n",
    "\n",
    "west = risk[risk['state'].isin([\"AK\", \"AZ\", \"CA\" ,\"CO\" ,\"HI\" ,\"ID\" ,\"MT\" ,\"NM\", \"NV\" ,\"OR\" ,\"UT\" ,\"WA\", \"WY\"])]\n",
    "np.unique(west['state'])\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "id": "0e5d1b90"
   },
   "outputs": [],
   "source": [
    "west_INOUT= west[west['date']>='2020-06-10']\n",
    "west_risk_date= west_INOUT[west_INOUT['date']<='2020-06-24']\n",
    "west_risk_date_clm= west_risk_date[['fips', 'riskLevels.overall']]\n",
    "\n",
    "risk_level_AVG_Jun= west_risk_date_clm.groupby(['fips']).agg(['mean'])\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "id": "31d60503"
   },
   "outputs": [],
   "source": [
    "risk_level_AVG_Jun.to_csv(\"C:/Users/nimda/Desktop/Research_2/Data/New_Data/west_risk_level_10-24_6.csv\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "id": "2cf46ffc",
    "outputId": "990a1aad-b783-472a-c6ef-90283939787c"
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array(['CT', 'MA', 'ME', 'NH', 'NJ', 'NY', 'PA', 'RI', 'VT'], dtype=object)"
      ]
     },
     "execution_count": 6,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#Northeast \"CT\" \"MA\" \"ME\" \"NH\" \"NJ\" \"NY\" \"PA\" \"RI\" \"VT\"\n",
    "\n",
    "\n",
    "north = risk[risk['state'].isin([\"CT\", \"MA\", \"ME\",\"NH\", \"NJ\", \"NY\" ,\"PA\", \"RI\" ,\"VT\"])]\n",
    "np.unique(north['state'])\n",
    "\n",
    "\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "id": "cf2487e2"
   },
   "outputs": [],
   "source": [
    "north_INOUT= north[north['date']>='2020-03-15']\n",
    "north_risk_date= north_INOUT[north_INOUT['date']<='2020-04-05']\n",
    "north_risk_date_clm= north_risk_date[['fips', 'riskLevels.overall']]\n",
    "\n",
    "risk_level_march= north_risk_date_clm.groupby(['fips']).agg(['mean'])\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "id": "d0d2d8e1"
   },
   "outputs": [],
   "source": [
    "risk_level_march.to_csv(\"C:/Users/nimda/Desktop/Research_2/Data/New_Data/north_risk_march.csv\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "id": "6218c03a",
    "outputId": "29cb2fc1-7604-4c5c-89e3-cfbf2cd4d25e"
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array(['AL', 'AR', 'DC', 'DE', 'FL', 'GA', 'KY', 'LA', 'MD', 'MS', 'NC',\n",
       "       'OK', 'SC', 'TN', 'TX', 'VA', 'WV'], dtype=object)"
      ]
     },
     "execution_count": 10,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "###########South \n",
    "south = risk[risk['state'].isin([\"AL\",\"AR\", \"DC\" ,\"DE\" ,\"FL\" ,\"GA\", \"KY\", \"LA\" ,\"MD\", \"MS\", \"NC\", \"OK\" ,\"SC\", \"TN\", \"TX\" ,\"VA\", \"WV\"\n",
    "])]\n",
    "np.unique(south['state'])\n",
    "\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "id": "f56066c6"
   },
   "outputs": [],
   "source": [
    "south_INOUT= south[south['date']>='2020-04-20']\n",
    "south_risk_date= south_INOUT[south_INOUT['date']<='2020-05-05']\n",
    "south_risk_date_clm= south_risk_date[['fips', 'riskLevels.overall']]\n",
    "\n",
    "risk_level_may= south_risk_date_clm.groupby(['fips']).agg(['mean'])\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "id": "3d9d8ebb"
   },
   "outputs": [],
   "source": [
    "risk_level_may.to_csv(\"C:/Users/nimda/Desktop/Research_2/Data/New_Data/south_risk_may.csv\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "id": "5a404b5e"
   },
   "outputs": [],
   "source": [
    "#USA\n",
    "\n",
    "us_INOUT= risk[risk['date']>='2020-06-20']\n",
    "us_risk_date= us_INOUT[us_INOUT['date']<='2020-07-04']\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "id": "5147cbb0"
   },
   "outputs": [],
   "source": [
    "us_risk_date_clm= us_risk_date[['fips', 'riskLevels.overall']]\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "id": "64e370e4"
   },
   "outputs": [],
   "source": [
    "risk_level_AVG_nov= us_risk_date_clm.groupby(['fips']).agg(['mean'])\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "id": "e1116bfd"
   },
   "outputs": [],
   "source": [
    "risk_level_AVG_nov.to_csv(\"C:/Users/nimda/Desktop/Research_2/Data/New_Data/us_risk_level_20_6_4_7.csv\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "id": "857c8558"
   },
   "outputs": [],
   "source": []
  }
 ],
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